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Record W4387809850 · doi:10.3389/fcosc.2023.1277254

Framework features enabling faster establishment and better management of privately protected areas in New South Wales, Australia

2023· article· en· W4387809850 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Conservation Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsnot available
FundersNew South Wales GovernmentNSW Office of Environment and Heritage
KeywordsConvention on Biological DiversityLegislationBiodiversityEnvironmental resource managementGovernment (linguistics)GeographyEnvironmental planningEnvironmental protectionBusinessEcologyPolitical science

Abstract

fetched live from OpenAlex

In response to the Convention on Biological Diversity’s Kunming-Montreal Global Biodiversity Framework, Australia has committed to protecting 30 per cent of lands and oceans for nature conservation by 2030. Privately protected areas are vital to meeting this target and establishing an ecologically representative and well-connected National Reserve System on land in Australia. As a federated nation, most public and privately protected areas (especially conservation covenants) are established under state or territory (i.e. subnational) legislation, as opposed to national legislation. This paper conducts a review of changes in policy and practice for private land conservation in the state of New South Wales (NSW) that has led to a marked acceleration in the establishment of privately protected areas since 2017. The historical average rate at which privately protected areas were being established in NSW under various schemes prior to the changes in 2017 was about 50 agreements and 12,000 hectares per annum. The new Biodiversity Conservation Act 2016 , the Biodiversity Conservation Trust of NSW (BCT), and increased NSW Government funding commenced in August 2017. Since then, the rate of establishment of privately protected areas has accelerated to more than 100 agreements and 45,000 hectares per annum. Not only has the rate of establishment more than tripled (by area) but many more privately protected areas are being established in higher priority bioregions, and the BCT is now able to provide better financial and technical support to privately protected areas, leading to better conservation outcomes overall. Key changes that have strengthened the framework for establishing and managing privately protected areas in NSW include a guide for strategic investment; institutional arrangements that foster effective governance, trust and transparency; substantive NSW Government funding; an accumulating endowment fund model; in-perpetuity payments; and faster and more targeted delivery mechanisms. The paper highlights features that could be adopted in other jurisdictions in Australia to support the vital role that privately protected areas must play in achieving commitments to nature conservation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.267
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it